Systematic Temperature and Precipitation Biases in the CLARIS-LPB Ensemble Simulations over South America and Possible Implications for Climate Change Projections

SILVINA A SOLMAN

Sao Jose dos Campos

Workshop; IPCC Workshop on Regional Climate Projections and their Use in Impacts and Risk Analysis Studies; 2015

IPCC

Within the framework of the CLARIS-LPB EU Project, a suite of 7 coordinated Regional Climate Model (RCM) simulations over South America (SA) driven by both the ERA-Interim reanalysis and a set of CMIP3 Global Climate Models were performed. The ability of the ERA-Interim driven RCMs in reproducing the observed climate conditions was evaluated in a recent study (Solman et al., 2013) and several systematic biases were identified. In particular, most RCMs showed a systematic temperature overestimation and precipitation underestimation over the La Plata Basin (LPB) region. However, for the scenario projection analysis the RCMs are driven by GCMs, so that errors in the large scale forcing, inherited through the boundary conditions, may combine with the errors in the RCM itself. Consequently, exploring both reanalysis- driven and GCM-driven RCM simulations is necessary in order to quantify RCMs performance under current climate conditions and to identify the source of RCM errors. Moreover, exploring the behaviour of model biases may help in interpreting the potential impact of model biases on the future climate projections and also in developing strategies for bias correction. In this context, the focus of this study twofold. First, to characterize the biases in simulating the mean temperature and precipitation in the CLARIS-LPB ensemble in order to identify whether the model biases are GCM or RCM dependent, which would help identifying possible paths for model improvements. Second, to evaluate the bias behaviour in order to determine how the bias may affect the future climate change signal.